Figure 1

Total Time

Orientation Time

Distance

Speed

Dwell Time

Teleportations

Figure 2

Figure 2 Plots

Total Time

Distance

Figure 2 Stats

Total Time

## Type III Analysis of Variance Table with Satterthwaite's method
##           Sum Sq Mean Sq NumDF DenDF F value    Pr(>F)    
## Block_num  19558  9778.9     2    50  94.469 < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Type III Analysis of Variance Table with Satterthwaite's method
##           Sum Sq Mean Sq NumDF DenDF F value    Pr(>F)    
## Block_num  56197   28099     2    40  21.669 4.211e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Type III Analysis of Variance Table with Satterthwaite's method
##               Sum Sq Mean Sq NumDF DenDF F value    Pr(>F)    
## Block_num      72764   36382     2    90 57.3998 < 2.2e-16 ***
## Age            21165   21165     1    45 33.3916 6.649e-07 ***
## Block_num:Age   6888    3444     2    90  5.4339  0.005917 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Distance

## Type III Analysis of Variance Table with Satterthwaite's method
##           Sum Sq Mean Sq NumDF DenDF F value    Pr(>F)    
## Block_num 328941  164471     2    50   47.81 2.476e-12 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Type III Analysis of Variance Table with Satterthwaite's method
##           Sum Sq Mean Sq NumDF DenDF F value    Pr(>F)    
## Block_num 486099  243050     2    40  12.096 7.793e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure 3

Total Time Correlations

corr_ct_ya <- cor.test(data_ya_mean$Total_Time, data_ya_mean$NARA)
corr_ct_ya
## 
##  Pearson's product-moment correlation
## 
## data:  data_ya_mean$Total_Time and data_ya_mean$NARA
## t = -2.1853, df = 24, p-value = 0.03886
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.68641361 -0.02377631
## sample estimates:
##        cor 
## -0.4073764

corr_ct_oa <- cor.test(data_oa_mean$Total_Time, data_oa_mean$NARA)
corr_ct_oa
## 
##  Pearson's product-moment correlation
## 
## data:  data_oa_mean$Total_Time and data_oa_mean$NARA
## t = -4.075, df = 19, p-value = 0.0006456
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.8608260 -0.3562548
## sample estimates:
##        cor 
## -0.6829156

Distance Correlations

corr_dt_ya <- cor.test(data_ya_mean$Distance, data_ya_mean$NARA)
corr_dt_ya
## 
##  Pearson's product-moment correlation
## 
## data:  data_ya_mean$Distance and data_ya_mean$NARA
## t = -3.1643, df = 24, p-value = 0.004187
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.7684277 -0.1965251
## sample estimates:
##       cor 
## -0.542574

corr_dt_oa <- cor.test(data_oa_mean$Distance, data_oa_mean$NARA)
corr_dt_oa
## 
##  Pearson's product-moment correlation
## 
## data:  data_oa_mean$Distance and data_oa_mean$NARA
## t = -4.0828, df = 19, p-value = 0.0006342
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.8611634 -0.3573930
## sample estimates:
##       cor 
## -0.683611

NARA Scores

##             Df Sum Sq Mean Sq F value  Pr(>F)   
## Age          1   5998    5998   10.06 0.00273 **
## Residuals   45  26833     596                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Extra